


import json
import os
import unittest

from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin







@require_tokenizers
class 							lowerCamelCase__						(				UpperCAmelCase       ,						unittest.TestCase   ):






			"""simple docstring"""






			_UpperCamelCase		:       Dict 			=		GPTaTokenizer
			_UpperCamelCase		:       str 			=		GPTaTokenizerFast
			_UpperCamelCase		:       Tuple 			=		True
			_UpperCamelCase		:       Dict 			=		{'add_prefix_space': True}
			_UpperCamelCase		:       Optional[Any] 			=		False




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						super().setUp()

						# Adapted from Sennrich et al. 2015 and https://github.com/rsennrich/subword-nmt
						UpperCamelCase__       =							[
						    "l",
						    "o",
						    "w",
						    "e",
						    "r",
						    "s",
						    "t",
						    "i",
						    "d",
						    "n",
						    "\u0120",
						    "\u0120l",
						    "\u0120n",
						    "\u0120lo",
						    "\u0120low",
						    "er",
						    "\u0120lowest",
						    "\u0120newer",
						    "\u0120wider",
						    "<unk>",
						    "<|endoftext|>",
						]
						UpperCamelCase__       =							dict(zip(snake_case   ,    range(len(snake_case  )  )  )  )
						UpperCamelCase__       =							["#version: 0.2", "\u0120 l", "\u0120l o", "\u0120lo w", "e r", ""]
						UpperCamelCase__       =							{"unk_token": "<unk>"}

						UpperCamelCase__       =							os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES["vocab_file"]  )
						UpperCamelCase__       =							os.path.join(self.tmpdirname   ,    VOCAB_FILES_NAMES["merges_file"]  )
						with open(self.vocab_file   ,    "w"   ,    encoding="utf-8"  ) as fp:
									fp.write(json.dumps(snake_case  ) + "\n"  )
						with open(self.merges_file   ,    "w"   ,    encoding="utf-8"  ) as fp:
									fp.write("\n".join(snake_case  )  )




			def 					snake_case__					(				self   ,    **snake_case  ):

						'''simple docstring'''


						kwargs.update(self.special_tokens_map  )
						return GPTaTokenizer.from_pretrained(self.tmpdirname   ,    **snake_case  )




			def 					snake_case__					(				self   ,    **snake_case  ):

						'''simple docstring'''


						kwargs.update(self.special_tokens_map  )
						return GPTaTokenizerFast.from_pretrained(self.tmpdirname   ,    **snake_case  )




			def 					snake_case__					(				self   ,    snake_case  ):

						'''simple docstring'''


						UpperCamelCase__       =							"lower newer"
						UpperCamelCase__       =							"lower newer"
						return input_text, output_text




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							GPTaTokenizer(self.vocab_file   ,    self.merges_file   ,    **self.special_tokens_map  )
						UpperCamelCase__       =							"lower newer"
						UpperCamelCase__       =							["\u0120low", "er", "\u0120", "n", "e", "w", "er"]
						UpperCamelCase__       =							tokenizer.tokenize(snake_case   ,    add_prefix_space=snake_case  )
						self.assertListEqual(snake_case   ,    snake_case  )

						UpperCamelCase__       =							tokens + [tokenizer.unk_token]
						UpperCamelCase__       =							[14, 15, 10, 9, 3, 2, 15, 19]
						self.assertListEqual(tokenizer.convert_tokens_to_ids(snake_case  )   ,    snake_case  )




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						if not self.test_rust_tokenizer:
									return

						UpperCamelCase__       =							self.get_tokenizer()
						UpperCamelCase__       =							self.get_rust_tokenizer(add_prefix_space=snake_case  )

						UpperCamelCase__       =							"lower newer"

						# Testing tokenization
						UpperCamelCase__       =							tokenizer.tokenize(snake_case   ,    add_prefix_space=snake_case  )
						UpperCamelCase__       =							rust_tokenizer.tokenize(snake_case  )
						self.assertListEqual(snake_case   ,    snake_case  )

						# Testing conversion to ids without special tokens
						UpperCamelCase__       =							tokenizer.encode(snake_case   ,    add_special_tokens=snake_case   ,    add_prefix_space=snake_case  )
						UpperCamelCase__       =							rust_tokenizer.encode(snake_case   ,    add_special_tokens=snake_case  )
						self.assertListEqual(snake_case   ,    snake_case  )

						# Testing conversion to ids with special tokens
						UpperCamelCase__       =							self.get_rust_tokenizer(add_prefix_space=snake_case  )
						UpperCamelCase__       =							tokenizer.encode(snake_case   ,    add_prefix_space=snake_case  )
						UpperCamelCase__       =							rust_tokenizer.encode(snake_case  )
						self.assertListEqual(snake_case   ,    snake_case  )

						# Testing the unknown token
						UpperCamelCase__       =							tokens + [rust_tokenizer.unk_token]
						UpperCamelCase__       =							[14, 15, 10, 9, 3, 2, 15, 19]
						self.assertListEqual(rust_tokenizer.convert_tokens_to_ids(snake_case  )   ,    snake_case  )




			def 					snake_case__					(				self   ,    *snake_case   ,    **snake_case  ):

						'''simple docstring'''


						pass




			def 					snake_case__					(				self   ,    snake_case=15  ):

						'''simple docstring'''


						for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
									with self.subTest(F'''{tokenizer.__class__.__name__} ({pretrained_name})'''  ):
												UpperCamelCase__       =							self.rust_tokenizer_class.from_pretrained(snake_case   ,    **snake_case  )

												# Simple input
												UpperCamelCase__       =							"This is a simple input"
												UpperCamelCase__       =							["This is a simple input 1", "This is a simple input 2"]
												UpperCamelCase__       =							("This is a simple input", "This is a pair")
												UpperCamelCase__       =							[
												    ("This is a simple input 1", "This is a simple input 2"),
												    ("This is a simple pair 1", "This is a simple pair 2"),
												]

												# Simple input tests
												self.assertRaises(snake_case   ,    tokenizer_r.encode   ,    snake_case   ,    max_length=snake_case   ,    padding="max_length"  )

												# Simple input
												self.assertRaises(snake_case   ,    tokenizer_r.encode_plus   ,    snake_case   ,    max_length=snake_case   ,    padding="max_length"  )

												# Simple input
												self.assertRaises(
												    snake_case   ,    tokenizer_r.batch_encode_plus   ,    snake_case   ,    max_length=snake_case   ,    padding="max_length"   ,    )

												# Pair input
												self.assertRaises(snake_case   ,    tokenizer_r.encode   ,    snake_case   ,    max_length=snake_case   ,    padding="max_length"  )

												# Pair input
												self.assertRaises(snake_case   ,    tokenizer_r.encode_plus   ,    snake_case   ,    max_length=snake_case   ,    padding="max_length"  )

												# Pair input
												self.assertRaises(
												    snake_case   ,    tokenizer_r.batch_encode_plus   ,    snake_case   ,    max_length=snake_case   ,    padding="max_length"   ,    )




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							GPTaTokenizer.from_pretrained(self.tmpdirname   ,    pad_token="<pad>"  )

						# Simple input
						UpperCamelCase__       =							"This is a simple input"
						UpperCamelCase__       =							["This is a simple input looooooooong", "This is a simple input"]
						UpperCamelCase__       =							("This is a simple input", "This is a pair")
						UpperCamelCase__       =							[
						    ("This is a simple input loooooong", "This is a simple input"),
						    ("This is a simple pair loooooong", "This is a simple pair"),
						]

						UpperCamelCase__       =							tokenizer.pad_token_id

						UpperCamelCase__       =							tokenizer(snake_case   ,    padding="max_length"   ,    max_length=30   ,    return_tensors="np"  )
						UpperCamelCase__       =							tokenizer(snake_case   ,    padding=snake_case   ,    truncate=snake_case   ,    return_tensors="np"  )
						UpperCamelCase__       =							tokenizer(*snake_case   ,    padding="max_length"   ,    max_length=60   ,    return_tensors="np"  )
						UpperCamelCase__       =							tokenizer(snake_case   ,    padding=snake_case   ,    truncate=snake_case   ,    return_tensors="np"  )

						# s
						# test single string max_length padding
						self.assertEqual(out_s["input_ids"].shape[-1]   ,    30  )
						self.assertTrue(pad_token_id in out_s["input_ids"]  )
						self.assertTrue(0 in out_s["attention_mask"]  )

						# s2
						# test automatic padding
						self.assertEqual(out_sa["input_ids"].shape[-1]   ,    33  )
						# long slice doesn't have padding
						self.assertFalse(pad_token_id in out_sa["input_ids"][0]  )
						self.assertFalse(0 in out_sa["attention_mask"][0]  )
						# short slice does have padding
						self.assertTrue(pad_token_id in out_sa["input_ids"][1]  )
						self.assertTrue(0 in out_sa["attention_mask"][1]  )

						# p
						# test single pair max_length padding
						self.assertEqual(out_p["input_ids"].shape[-1]   ,    60  )
						self.assertTrue(pad_token_id in out_p["input_ids"]  )
						self.assertTrue(0 in out_p["attention_mask"]  )

						# p2
						# test automatic padding pair
						self.assertEqual(out_pa["input_ids"].shape[-1]   ,    52  )
						# long slice pair doesn't have padding
						self.assertFalse(pad_token_id in out_pa["input_ids"][0]  )
						self.assertFalse(0 in out_pa["attention_mask"][0]  )
						# short slice pair does have padding
						self.assertTrue(pad_token_id in out_pa["input_ids"][1]  )
						self.assertTrue(0 in out_pa["attention_mask"][1]  )




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							"$$$"
						UpperCamelCase__       =							GPTaTokenizer.from_pretrained(self.tmpdirname   ,    bos_token=snake_case   ,    add_bos_token=snake_case  )

						UpperCamelCase__       =							"This is a simple input"
						UpperCamelCase__       =							["This is a simple input 1", "This is a simple input 2"]

						UpperCamelCase__       =							tokenizer.bos_token_id

						UpperCamelCase__       =							tokenizer(snake_case  )
						UpperCamelCase__       =							tokenizer(snake_case  )

						self.assertEqual(out_s.input_ids[0]   ,    snake_case  )
						self.assertTrue(all(o[0] == bos_token_id for o in out_sa.input_ids  )  )

						UpperCamelCase__       =							tokenizer.decode(out_s.input_ids  )
						UpperCamelCase__       =							tokenizer.batch_decode(out_sa.input_ids  )

						self.assertEqual(decode_s.split()[0]   ,    snake_case  )
						self.assertTrue(all(d.split()[0] == bos_token for d in decode_sa  )  )




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						pass







			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							[self.get_tokenizer(do_lower_case=snake_case   ,    add_bos_token=snake_case  )]
						for tokenizer in tokenizers:
									with self.subTest(F'''{tokenizer.__class__.__name__}'''  ):
												UpperCamelCase__       =							"Encode this."
												UpperCamelCase__       =							"This one too please."
												UpperCamelCase__       =							tokenizer.encode(snake_case   ,    add_special_tokens=snake_case  )
												encoded_sequence += tokenizer.encode(snake_case   ,    add_special_tokens=snake_case  )
												UpperCamelCase__       =							tokenizer.encode_plus(
												    snake_case   ,    snake_case   ,    add_special_tokens=snake_case   ,    return_special_tokens_mask=snake_case   ,    )
												UpperCamelCase__       =							encoded_sequence_dict["input_ids"]
												UpperCamelCase__       =							encoded_sequence_dict["special_tokens_mask"]
												self.assertEqual(len(snake_case  )   ,    len(snake_case  )  )

												UpperCamelCase__       =							[
												    (x if not special_tokens_mask[i] else None) for i, x in enumerate(snake_case  )
												]
												UpperCamelCase__       =							[x for x in filtered_sequence if x is not None]
												self.assertEqual(snake_case   ,    snake_case  )







@require_tokenizers
class 							lowerCamelCase__						(				unittest.TestCase   ):






			"""simple docstring"""






			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							AutoTokenizer.from_pretrained("facebook/opt-350m"   ,    from_slow=snake_case  )
						UpperCamelCase__       =							"A photo of a cat"

						UpperCamelCase__       =							tokenizer.encode(
						    snake_case   ,    )
						self.assertEqual(snake_case   ,    [2, 250, 1345, 9, 10, 4758]  )
						tokenizer.save_pretrained("test_opt"  )

						UpperCamelCase__       =							AutoTokenizer.from_pretrained("./test_opt"  )
						UpperCamelCase__       =							tokenizer.encode(
						    snake_case   ,    )
						self.assertEqual(snake_case   ,    [2, 250, 1345, 9, 10, 4758]  )




			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							AutoTokenizer.from_pretrained("facebook/opt-350m"   ,    use_slow=snake_case  )
						UpperCamelCase__       =							"A photo of a cat"

						UpperCamelCase__       =							tokenizer.encode(
						    snake_case   ,    )
						# Same as above
						self.assertEqual(snake_case   ,    [2, 250, 1345, 9, 10, 4758]  )







			@unittest.skip("This test is failing because of a bug in the fast tokenizer"  )
			def 					snake_case__					(				self  ):

						'''simple docstring'''


						UpperCamelCase__       =							AutoTokenizer.from_pretrained("facebook/opt-350m"   ,    from_slow=snake_case  )

						UpperCamelCase__       =							"bos"
						UpperCamelCase__       =							tokenizer.get_vocab()["bos"]

						UpperCamelCase__       =							"A photo of a cat"
						UpperCamelCase__       =							tokenizer.encode(
						    snake_case   ,    )
						# We changed the bos token
						self.assertEqual(snake_case   ,    [31957, 250, 1345, 9, 10, 4758]  )
						tokenizer.save_pretrained("./tok"  )
						UpperCamelCase__       =							AutoTokenizer.from_pretrained("./tok"  )
						self.assertTrue(tokenizer.is_fast  )
						UpperCamelCase__       =							tokenizer.encode(
						    snake_case   ,    )
						self.assertEqual(snake_case   ,    [31957, 250, 1345, 9, 10, 4758]  )






def 							UpperCamelCase_(					_A :Union[str, Any]	)->		List[str]:
			UpperCamelCase__       =							[0] * len(_A	)
			UpperCamelCase__       =							[]
			UpperCamelCase__       =							[]
			UpperCamelCase__       =							0

			for values in graph.values():
						for i in values:
									indegree[i] += 1

			for i in range(len(_A	)	):
						if indegree[i] == 0:
									queue.append(_A	)

			while queue:
						UpperCamelCase__       =							queue.pop(0	)
						cnt += 1
						topo.append(_A	)
						for x in graph[vertex]:
									indegree[x] -= 1
									if indegree[x] == 0:
												queue.append(_A	)

			if cnt != len(_A	):
						print("Cycle exists"	)
			else:
						print(_A	)


# Adjacency List of Graph
__UpperCamelCase     		=							{0: [1, 2], 1: [3], 2: [3], 3: [4, 5], 4: [], 5: []}







topological_sort(graph)


